1. Technical Field
The invention relates to determining the concentration of a target analyte in a sample. More particularly, the invention relates to a method and apparatus for generating basis sets for use in determining the concentration of a target analyte in a sample, for example using multi-spectral analysis.
2. Description of the Prior Art
Data analysis during spectroscopic analysis refers to the process of finding optimum wavelengths and generating accurate calibrations to relate a given set of spectroscopic data to reference laboratory values for the composition of a set of samples, such that it is possible to analyze, i.e. predict, the values of future samples of unknown composition. Calibration of spectroscopic instruments that are used to perform spectroscopic measurements is typically accomplished by application of multiple regression of the absorbance at some number of wavelengths against the reference laboratory values, i.e. mathematically determining the best possible fit of a straight line to a set of data (see, for example, H. Mark, Principles and Practice of Spectroscopic Calibration, John Wiley & Sons, Inc. (1991)).
An error free calibration, i.e. a sample for which Beer's law applies, is one in which the constituent of interest, and which is the only constituent in the sample, is dissolved in a completely nonabsorbing solvent, and has only a single absorbance band. In this case, the concentration of the constituent is known exactly over a broad range for the set of calibration samples; and the spectrometer has no noise, nonlinearity, or other fault. In such an idealized case, the height of the absorbance peak is strictly proportional to the concentration of the constituent. Thus, it is possible to calibrate a system using only two samples because two points determine the line, and the slope of the line and intercept of data are readily determined using known mathematical formulae.
Unfortunately, the ideal case does not prevail in the real world. For example, spectroscopic measurements are subject to such phenomena as skew in the data, which is caused by physical changes in the instrument, sample, or experiment. For example, interfering and/or dominating constituents in the sample other than the constituent of interest can affect the data. Temperature, medium, pathlength, and scattering effects must also be considered.
Near-infrared (near-IR) absorbance spectra of liquid samples contain a large amount of information about the various organic constituents of the sample. Specifically, the vibrational, rotational, and stretching energy associated with organic molecular structures (e.g. carbon-hydrogen, oxygen-hydrogen, and nitrogen-hydrogen chemical bonds) produce perturbations in the near-IR region which can be detected and related to the concentration of various organic constituents present in the sample. However, in complex sample matrices, near-IR spectra also contain an appreciable amount of interference, due in part to similarities of structure amongst analytes, relative levels of analyte concentration, interfering relationships between analytes, and the magnitude of electronic and chemical noise inherent in a particular system. Such interference reduces the efficiency and precision of measurements obtained using near-IR spectrometry to determine the concentration of liquid sample analyses.
For example, temperature is a critical parameter for near-IR spectroscopic analysis of aqueous based samples. Major water absorption bands are centered at approximately 3800, 5200, and 6900 nm, but the exact positions of these bands are temperature sensitive. These bands shift to higher frequencies at higher temperatures. Changes in temperature also alter the extent of water hydrogen bonding to other chemical species, which causes significant shifts in band positions. The large water content of most clinical samples, e.g. when determining glucose concentration in an aqueous solution, necessitates precise control of the sample temperature.
With regard to temperature, K. Hazen, M. Arnold, G. Small, Temperature-Insensitive Near-Infrared Spectroscopic Measurement of Glucose in Aqueous Solutions, Applied Spectroscopy, Vol. 48, No. 4, pp. 477-483 (1994) disclose the use of a digital Fourier filter that is combined with partial least squares (PLS) regression to generate a calibration model for glucose that is insensitive to sample temperature. The calibration model is initially created using spectra collected over the 5000 to 4000 nm spectral range with samples maintained at 37.degree. C. The model is evaluated by judging the ability to determine glucose concentrations from a set of prediction spectra. Absorption spectra in the prediction set are obtained by ratioing single-beam spectra collected from solutions at temperatures ranging from 32.degree. C. to 41.degree. C. to reference spectra collected at 37.degree. C. The temperature sensitivity of the underlying water absorption bands creates large baseline variations in the prediction spectra that are effectively eliminated by the Fourier filtering step.
See, also, G. Small, M. Arnold, L. Marquardt, Strategies for Coupling Digital Filtering with Partial Least-Squares Regression: Application to Determination of Glucose in Plasma by Fourier Transform Near-Infrared Spectroscopy, Analytical Chemistry, Vol. 65, No. 22, pp. 3279-3289 (1993) (Gaussian-shaped bandpass digital filters are implemented by use of Fourier filtering techniques and employed to preprocess spectra to remove variations due to the background absorbance of the [bovine] plasma matrix. PLS regression is used with the filtered spectra to compute calibration models for glucose); M. Arnold, G. Small, Determination of Physiological Levels of Glucose in an Aqueous Matrix with Digitally Filtered Fourier Transform Near-Infrared Spectra, Analytical Chemistry, Vol. 62, No. 14, pp. 1457-1464 (1990) (and G. Small, M. Arnold, Method and Apparatus for Non-Invasive Detection of Physiological Chemicals, Particularly Glucose, U.S. Pat. No. 5,459,317 (Oct. 17, 1995)) (. . . A digital Fourier filter . . . removes both high-frequency noise and low-frequency base-line variations from the spectra. Numerical optimization procedures are used to identify the best location and width of a Gaussian-shaped frequency response function for this Fourier filter. A dynamic area calculation, coupled with a simple linear base-line correction, provides an integrated area from the processed spectra that is linearly related to glucose concentration . . . ); and K. Hazen, Glucose Determination in Biological Matrices Using Near-infrared Spectroscopy, Ph.D. Thesis, Univ. of Iowa (August 1995) (glucose determinations in water, serum, blood, and the body are performed using near-IR spectroscopy, multivariate analysis is used to correlate minor spectral variations with analyte concentrations.
A number of near-IR devices and methods have been described that may be used in connection with the foregoing techniques to provide noninvasive blood analyte determinations:
U.S. Pat. No. 5,360,004 to Purdy et al. describes a method and apparatus for the determination of blood analyte concentrations, wherein a body portion is irradiated with radiation containing two or more distinct bands of continuous-wavelength incident radiation. Purdy et al. emphasize filtration techniques to specifically block radiation at the two peaks in the near-IR absorption spectrum for water, occurring at about 1440 and 1935 nm. Such selective blocking is carried out in order to avoid a heating effect that may be due to the absorption of radiation by water in the body part being irradiated.
By contrast, U.S. Pat. No. 5,267,152 to Yang et al. describes noninvasive devices and techniques for measuring blood glucose concentration using only the portion of the IR spectrum which contains the near-IR water absorption peaks (e.g. the water transmission window, which includes those wavelengths between 1300 and 1900 nm), where water absorbance reaches a minimum at 1600 nm. Optically controlled light is directed to a tissue source and then collected by an integrating sphere. The collected light is analyzed and blood glucose concentration calculated using a stored reference calibration curve.
U.S. Pat. No. 5,606,164 to Price et al. describes a method and apparatus for measuring the concentration of an analyte present in a biological fluid, near-IR radiation is applied to calibration samples to produce calibration data. Unknown sample data is analyzed using data pretreatment followed by projection into the calibration model space with prediction of analyte concentration using the calibration model.
Devices have also been described for use in determination of analyte concentrations in complex samples, for example:
U.S. Pat. No. 5,242,602 to Richardson et al. describes methods for analyzing aqueous systems to detect multiple components. The methods involve determination of the absorbance or emission spectrum of the components over the range of 200 to 2500 nm, and application of chemometrics algorithms to extract segments of the spectral data obtained to quantify multiple performance indicators.
U.S. Pat. No. 5,252,829 to Nygaard et al. describes a method and apparatus for measuring the concentration of urea in a milk sample using an infrared attenuation measuring technique. Multivariate techniques are carried out to determine spectral contributions of known components using partial least squares algorithms, principal component regression, multiple linear regression or artificial neural network learning. Calibration is carried out by accounting for the component contributions that block the analyte signal of interest. Thus, Nygaard et al. describe a technique of measuring multiple analyte infrared attenuations and compensating for the influence of background analyses to obtain a more accurate measurement.
U.S. Pat. No. 4,975,581 to Robinson et al describes a method and apparatus for determining analyte concentration in a biological sample based on a comparison of infrared energy absorption (i.e. differences in absorption at several wavelengths) between a known analyte concentration and a sample. The comparison is performed using partial least squares analysis or other multivariate techniques.
U.S. Pat. No. 4,882,492 to Schlager describes a method and apparatus for noninvasive determination of blood analyte concentrations. Modulated IR radiation is directed against a tissue sample (e.g. an ear lobe) and either passed through the tissue or impinged on a skin surface where it is spectrally modified by a target analyte (glucose). The spectrally modified radiation is then split, wherein one portion is directed through a negative correlation cell and another through a reference cell. Intensity of the radiation passing through the cells are compared to determine analyte concentration in the sample.
U.S. Pat. No. 4,306,152 to Ross et al. describes an optical fluid analyzer designed to minimize the effect of background absorption (i.e. the overall or base level optical absorbance of the fluid sample) on the accuracy of measurement in a turbid sample or in a liquid sample which is otherwise difficult to analyze. The apparatus measures an optical signal at the characteristic optical absorption of a sample component of interest and another signal at a wavelength selected to approximate background absorption, and then subtracts to reduce the background component of the analyte dependent signal.
U.S. Pat. No. 4,893,253 to Lodder describes a method for analyzing intact capsules and tablets by using near-infrared reflectance spectroscopy. The method detects adulterants in capsules by obtaining spectra for a training set of unadulterated samples, representing each spectrum as a point in a hyperspace, creating a number of training set replicates and a bootstrap replicate distribution, calculating the center of the bootstrap replicate distribution, obtaining a spectrum for an adulterated sample, transforming the spectrum into a point in hyperspace, and identifying the adulterated sample as abnormal based on a relationship between the adulterated sampl's hyperspatial point and the bootstrap replication distribution. See, also, R. Rosenthal, L. Paynter, L. Mackie, Non-Invasive Measurement of Blood Glucose, U.S. Pat. No. 5,028,787 (Jul. 2, 1991) (A near-infrared quantitative analysis instrument and method non-invasively measures blood glucose by analyzing near-infrared energy following interactance with venous or arterial blood, or transmission through a blood containing body part.).
The accuracy of information obtained using the above described methods and devices is limited by the spectral interference caused by background, i.e. non-analyte, sample constituents that also have absorption spectra in the near-IR range. Appreciable levels of background noise represent an inherent system limitation particularly when very little analyte is present. In light of this limitation, attempts have been made to improve signal-to-noise ratios, e.g. by avoiding water absorption peaks to enable the use of increased radiation intensity, by reducing the amount of spectral information to be analyzed, or by using subtraction or compensation techniques based on an approximation of background absorption. As discussed above, these techniques have focused primarily upon examining all constituents of a spectra simultaneously. Although such techniques have provided some improvement, there remains a need to provide a method and apparatus for performing a more precise determination of the concentration of analytes, for example in a liquid matrix, i.e. where an accurate representation of each and every sample component is obtained during analysis.